GitLab

* Expand a bit the presentation of examples

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Address review comments
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Add minimum version check in examples

* Style

* No need for new line maybe?

* Add helpful comment

* reverted changes of logging and saving metrics

* added max_sample arguments

* fixed code

* white space diff

* reformetting code

* reformatted code

* updated logging and saving metrics

* space removal

* make executable

* make executable

* same for the template

* cleanup

* Pad to 8x for fp16 multiple choice example (#9752)

* Pad to 8x for fp16 squad trainer example (#9752)

* Pad to 8x for fp16 ner example (#9752)

* Pad to 8x for fp16 swag example (#9752)

* Pad to 8x for fp16 qa beam search example (#9752)

* Pad to 8x for fp16 qa example (#9752)

* Pad to 8x for fp16 seq2seq example (#9752)

* Pad to 8x for fp16 glue example (#9752)

* Pad to 8x for fp16 new ner example (#9752)

* update script template #9752

* Update examples/multiple-choice/run_swag.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update examples/question-answering/run_qa.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update examples/question-answering/run_qa_beam_search.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* improve code quality #9752
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Auto-resume training from checkpoint

* Update examples/text-classification/run_glue.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Roll out to other examples
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Switch metrics in run_ner to datasets

* Add flag to return all metrics

* Upstream (and rename) sortish_sampler

* Revert "Upstream (and rename) sortish_sampler"

This reverts commit e07d0dcf650c2bae36da011dd76c77a8bb4feb0d.

* Allow example to use a revision and work with private models

* Copy to other examples and template

* Styling

* Reorganize example folder

* Continue reorganization

* Change requirements for tests

* Final cleanup

* Finish regroup with tests all passing

* Copyright

* Requirements and readme

* Make a full link for the documentation

* Address review comments

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add symlink

* Reorg again

* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Adapt title

* Update to new strucutre

* Remove test

* Update READMEs
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Use word_ids to get labels in run_ner

* Add sanity check

* Fix run_ner script

* Pin datasets

* Remove old deprecated arguments
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Remove needless imports

* Fix tests
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* <small>tiny typo</small>

* Tokenizers: ability to load from model subfolder

* use subfolder for local files as well

* Uniformize model shortcut name => model id

* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

The new run_ner.py script tries to run prediction on the input
test set `datasets["test"]`, but it should be the tokenized set
`tokenized_datasets["test"]`

* s|multiple_gpu|multi_gpu|g; s|multigpu|multi_gpu|g'

* doc

* add a multi-gpu job for all example tests

* run only ported tests

* rename

* explain why env is re-activated on each step

* mark all unported/checked tests with @require_torch_non_multigpu_but_fix_me

* style

* Apply suggestions from code review
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Add new token classification example

* Remove txt file

* Add test

* With actual testing done

* Less warmup is better

* Update examples/token-classification/run_ner_new.py
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Address review comments

* Fix test

* Make Lysandre happy

* Last touches and rename

* Rename in tests

* Address review comments

* More run_ner -> run_ner_old
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* change TokenClassificationTask class methods to static methods

Since we do not require self in the class methods of TokenClassificationTask we should probably switch to static methods. Also, since the class TokenClassificationTask does not contain a constructor it is currently unusable as is. By switching to static methods this fixes the issue of having to document the intent of the broken class.

Also, since the get_labels and read_examples_from_file methods are ought to be implemented. Static method definitions are unchanged even after inheritance, which means that it can be overridden, similar to other class methods.

* Trigger Build
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Align TF NER example over the PT one

* Fix Dataset call

* Fix gradient accumulation training

* Apply style

* Address Sylvain's comments

* Address Sylvain's comments

* Apply style

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* Add more token classification examples

* POS tagging example

* Phrase chunking example

* PR review fixes

* Add conllu to third party list (used in token classification examples)